Promoting sustainability through green innovation adoption: a case of manufacturing industry

2021 ◽  
Author(s):  
Sajid Ullah ◽  
Farman Ullah Khan ◽  
Naveed Ahmad
Keyword(s):  
Manufacturing Industry ◽  
Innovation Adoption ◽  
Green Innovation

scholarly journals Government R&D Subsidies, Environmental Regulations, and Their Effect on Green Innovation Efficiency of Manufacturing Industry: Evidence from the Yangtze River Economic Belt of China

2020 ◽  
Vol 17 (4) ◽  
pp. 1330 ◽  
Author(s):  
Ming Yi ◽  
Yiqian Wang ◽  
Modan Yan ◽  
Lina Fu ◽  
Yao Zhang
Keyword(s):  
Yangtze River ◽  
Manufacturing Industry ◽  
Industrial Structure ◽  
Environmental Regulations ◽  
Significance Test ◽  
Efficiency Improvement ◽  
The Yangtze River ◽  
Green Innovation ◽  
Negative Effects ◽  
Interaction Terms

The Yangtze River Economic Belt is the most important manufacturing economic belt in China. The level of manufacturing green innovation efficiency of the Yangtze River Economic Belt directly affects the overall competitiveness of China’s manufacturing industry. With panel data from 11 provinces and cities along the Yangtze River Economic Belt in China for the period of 2008 to 2017, this paper applies the slacks-based measure (SBM)-data envelopment analysis (DEA) model and panel Tobit model to conduct an empirical study of the effects of government research and development subsidies and environmental regulations on the green innovation efficiency of the manufacturing industry of the Yangtze River Economic Belt. The results show that, firstly, government R&D subsidies and environmental regulations are both conducive to improving the green innovation efficiency of the manufacturing industry of the Yangtze River Economic Belt; secondly, because of the fact that the interaction terms between government R&D subsidies and environmental regulations failed to pass the significance test, the positive moderating effects of R&D subsidies on environmental regulations and green innovation efficiency of the manufacturing industry are not obvious; thirdly, in terms of control variables, strengthening agglomeration is the only factor that is positively correlated with green innovation efficiency improvement of the manufacturing industry. Enterprise scale and industrial structure have negative effects on green innovation efficiency improvement, and the openness of economy has no correlation with green innovation efficiency.

Impact of Green Innovation on Labor Productivity and its Determinants: an Analysis of the Korean Manufacturing Industry

2013 ◽  
Vol 23 (8) ◽  
pp. 567-576 ◽  
Author(s):  
Chungwon Woo ◽  
Yanghon Chung ◽  
Dongphil Chun ◽  
Seunghun Han ◽  
Dukhee Lee
Keyword(s):  
Labor Productivity ◽  
Manufacturing Industry ◽  
Green Innovation

Green innovation adoption in automotive supply chain: the Malaysian case

2015 ◽  
Vol 108 ◽  
pp. 1115-1122 ◽  
Author(s):  
Suhaiza Zailani ◽  
Kannan Govindan ◽  
Mohammad Iranmanesh ◽  
Mohd Rizaimy Shaharudin ◽  
Yia Sia Chong
Keyword(s):  
Supply Chain ◽  
Innovation Adoption ◽  
Green Innovation ◽  
Automotive Supply Chain ◽  
Automotive Supply

scholarly journals Environmental Regulation, Two-Way Foreign Direct Investment, and Green Innovation Efficiency in China’s Manufacturing Industry

2018 ◽  
Vol 15 (10) ◽  
pp. 2292 ◽  
Author(s):  
Zhijun Feng ◽  
Bo Zeng ◽  
Qian Ming
Keyword(s):  
Foreign Direct Investment ◽  
Panel Data ◽  
Environmental Regulation ◽  
Direct Investment ◽  
Manufacturing Industry ◽  
Green Innovation ◽  
Negative Effects ◽  
Positive Effects ◽  
The Impact ◽  
Positive Effect

This paper adopts 2009 to 2015 panel data from 27 manufacturing industries in China. A Super-SBM model is used to measure the green innovation efficiency (GIE) of China’s manufacturing industry. A panel data model is then built to systematically examine the impact of environmental regulation (ER) and two-way foreign direct investment (FDI) on the GIE of China’s manufacturing industry under a unified analysis framework. The results are as follows: (1) the overall level of the green innovation efficiency in China’s manufacturing is low, and there is still great potential for improvement. Considering industry heterogeneity, the green innovation efficiency of patent-intensive manufacturing is significantly higher than that of non-patent-intensive manufacturing; (2) in terms of the whole manufacturing industry, ER and the interaction between ER and outward foreign direct investment (OFDI) have significantly negative effects on GIE, OFDI has significantly positive effects on GIE. (3) when considering industry heterogeneity, for patent-intensive manufacturing, ER and the interaction between ER and inward foreign direct investment (IFDI) have significantly negative effects on GIE, while IFDI has significantly positive effect on GIE. For non-patent-intensive manufacturing, ER and the interaction between ER and OFDI have significantly negative effects on GIE, while IFDI and the interaction between ER and IFDI have significantly positive effects on GIE.

scholarly journals Mapping Interactions among Green Innovations Barriers in Manufacturing Industry Using Hybrid Methodology: Insights from a Developing Country

2021 ◽  
Vol 18 (15) ◽  
pp. 7885
Author(s):  
Sajid Ullah ◽  
Naveed Ahmad ◽  
Farman Ullah Khan ◽  
Alina Badulescu ◽  
Daniel Badulescu
Keyword(s):  
Delphi Method ◽  
Manufacturing Industry ◽  
Matrix Multiplication ◽  
Developed Countries ◽  
Fear Of Failure ◽  
Green Innovation ◽  
Interpretive Structural Modeling ◽  
Environmental Institutions ◽  
Environmental Deterioration ◽  
Three Phase

Recent years have witnessed continuous rise in adopting green innovations which is considered as an important organizational instrument to achieve profits by reducing environmental deterioration. However, green innovation in developing countries, especially in Pakistan, is surprisingly scant as compared to developed countries. This paper empirically investigated obstacles to green innovations in Pakistani manufacturing firms. Specifically, a novel three phase methodological framework was applied to investigate significant barriers and filtration by integrating Delphi method (DM), interpretive structural modeling (ISM), and cross-impact matrix multiplication applied to classification (MICMAC). Our results highlighted that lack of enforceable laws regarding returned goods and recycled products, lack of rules and regulations for green practices, and lack of collaboration with government and environmental institutions are most critical barriers. However, fear of failure about green innovation is least important barriers to green innovations adoption. This study offers interesting clues to promote green innovation in manufacturing industry.

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